10,633 research outputs found
and Production at Tevatron
We present results from CDF and D\O\ on and productions
in collisions at The goal of the analyses
is to test the non-abelian self-couplings of the , and photon, one of
the most direct consequences of the gauge symmetry. We
present direct measurements of couplings and limits on
and couplings, based on
and events, respectively, observed
during the 1992--1993 run of the Fermilab Tevatron Collider.Comment: 19pages, 6 figures appended in a uuencoded file. Invited talk given
at the International Symposium on Vector Boson Self-Interactions, UCLA,
February 1-3, 199
Modelling of self-piercing riveting with ale, cel and sph based on abaqus/explicit
SPR (Self-piercing riveting) is a cold forming process that is used to fasten together two or more sheets of different materials mechanically with a rivet. Also SPR emulates the results and quality of spot welding without many of the risks, such as toxic fumes, sparks and noise. Thus circumstanced, this technique is widely used on the various filed especially within automobile industry. SPR, in particular, is excellent for lightweight manufacturing and for precise working while dramatically reducing cost and production time. The process deformation depends on the sheet size, shape of die, material flow, stiffness, etc. Also material deformation in both of rivet and workpiece sheets is tremendous large, for instance thinning, necking, shear and penetration. Therefore it is very hard to analyze this forming process with FEM which uses normal stress element formulation due to the collapse. On the other hand, Abaqus/Explicit has superb analysis methods, for example ALE, CEL and SPH[1]. This paper investigates several Abaqus/Explicit modeling techniques for simulating and optimizing SPR process. In addition, the effectiveness of these analysis methods was discussed and compared for evaluating SPR process forming in order to achieve an optimal die, material properties and suitability of deformations
Filtering and identification of stochastic volatility for parabolic type factor models
We consider the dynamics of forward rate process which is modeled by a parabolic type infinite-dimensional factor model with stochastic volatility. The parameters included in the stochastic volatility dynamics are estimated from the factor process as the observation data. Based on the maximum likelihood technique, we propose the off-line identification scheme and provide some numerical examples
Adaptive filtering for stochastic risk premia in bond market
We consider the adaptive filtering problem for estimating the randomly changing risk premium and its system parameters for zero-coupon bond models. The term structure model for a zero-coupon bond is formulated including the stochastic risk-premium factor. We specify our observation data from the yield curve and bond data which are used to hedge some option claims. For the xed system parameters, the Kalman filter for the risk-premium and the factor process is constructed first. Secondly, by using the parallel filtering technique and resampling technique commonly used in particle filters, the on-line estimation algorithm for model parameters is constructed. Some simulation studies are nally presented
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